A NEW APPROACH BASED ON THE SEROLOGICAL TESTS FOR THE DIAGNOSIS OF TUBERCULOSIS IN CATTLE

The diagnosis of bovine tuberculosis (TB) is still a challenge for a better control of the disease. Here we report the use of a simple ELISA test combined with a multilayer neuronal network analyzing method in order to diagnose TB in cattle from the north part of Tunisia. A panel of Mycobacterium bovis (Mbv)-specific recombinant proteins along with crud extracts were used to coat the 96 wells plates, namely the recombinant 10 kDa culture filtrate antigen (CFP-10), the 6 kD Early Secretory Antigenic Target (ESAT-6), the recombinant Esat-6/CFP-10 heterodimer along with the crud BCG proteins and Tuberculin purified protein derivative (PPD). In the current article, a new approach is described to compare their characterization degree to select the most discriminative antigens. The classification of subjects into two groups: TB+ and TB- subjects was affected by an artificial multilayer neural network and the statistical study to estimate the diagnosis of bovine tuberculosis and construct an optimal partition of the results. This method was applied on the serological tests of a set of cattles. The results are encouraging.